1. Technical Field
This invention relates generally to digital coding systems. More particularly, this invention relates to input transformation systems for speech coding.
2. Related Art
Telecommunication systems include both landline and wireless radio systems. Wireless telecommunication systems use radio frequency (RD.) communication. Currently, the frequencies available for wireless systems are centered in frequency ranges around 900 MHz and 1900 MHz. The expanding popularity of wireless communication devices, such as cellular telephones is increasing the RD. traffic in these frequency ranges. Reduced bandwidth communication would permit more data and voice transmissions in these frequency ranges, enabling the wireless system to allocate resources to a larger number of users.
Wireless systems may transmit digital or analog data. Digital transmission, however, has greater noise immunity and reliability than analog transmission. Digital transmission also provides more compact equipment and the ability to implement sophisticated signal processing functions. In the digital transmission of speech signals, an analog-to-digital converter samples an analog speech waveform. The digitally converted waveform is compressed (encoded) for transmission. The encoded signal is received and decompressed (decoded). After digital-to-analog conversion, the reconstructed speech is played in an earpiece, loudspeaker, or the like.
The analog-to-digital converter uses a large number of bits to represent the analog speech waveform. This larger number of bits creates a relatively large bandwidth. Speech compression reduces the number of bits that represent the speech signal, thus reducing the bandwidth needed for transmission. However, speech compression may result in degradation of the quality of decompressed speech. In general, a higher bit rate results in a higher quality, while a lower bit rate results in a lower quality.
Modern speech compression techniques (coding techniques) produce decompressed speech of relatively high quality at relatively low bit rates. One coding technique attempts to represent the perceptually important features of the speech signal without preserving the actual speech waveform at a constant bit-rate. Another coding technique, a variable-bit rate encoder, varies the degree of speech compression depending on the part of the speech signal being compressed. Typically, perceptually important parts of speech (e.g., voiced speech, plosives, or voiced onsets) are coded with a higher number of bits. Perceptually less critical parts of speech (e.g., unvoiced parts or silence between words) are coded with a lower number of bits. The resulting average of the varying bit rates may be relatively lower than a fixed bit rate providing decompressed speech of similar quality. These speech compression techniques lower the amount of bandwidth required to digitally transmit a speech signal.
During speech coding, these speech compression techniques also code “silence noise” in addition to the voice and other sounds received on an input signal. Silence noise typically includes very low-level ambient noise or sounds such as electronic circuit noise induced in the analog path of the input or speech signal before analog to digital conversion. Silence noise generally has very low amplitude. However, many companding operations such as those using A-law and μ-law have poor resolution at very low levels. Silence noise becomes amplified and thus an annoying component of the speech input signal to the speech coding system. If not removed from the input or speech signal prior to speech coding, silence noise becomes more annoying with decreasing bit-rate. The annoying effect of silence noise becomes compounded in configurations such as a typical PSTN where companding typically precedes and succeeds the speech coding.